Optimizing DevOps Pipelines with Performance Testing: A Comprehensive Approach |
||
 |
 |
|
| © 2023 by IJCTT Journal | ||
| Volume-71 Issue-6 |
||
| Year of Publication : 2023 | ||
| Authors : Vivek Basavegowda Ramu | ||
| DOI : 10.14445/22312803/IJCTT-V71I6P106 | ||
How to Cite?
Vivek Basavegowda Ramu, "Optimizing DevOps Pipelines with Performance Testing: A Comprehensive Approach," International Journal of Computer Trends and Technology, vol. 71, no. 6, pp. 35-41, 2023. Crossref, https://doi.org/10.14445/22312803/IJCTT-V71I6P106
Abstract
In the rapidly evolving software development landscape, integrating performance testing within DevOps pipelines has become crucial for ensuring the delivery of high-quality and efficient software systems. This research paper presents a comprehensive approach to optimizing DevOps pipelines by effectively incorporating performance testing. By leveraging performance testing techniques and methodologies throughout the development lifecycle, organizations can proactively identify and address performance bottlenecks, scalability challenges, and potential issues that may impact user experience and system stability. This study conducts a thorough literature review, explores best practices, and proposes practical strategies for integrating performance testing seamlessly into DevOps practices. Through the application of case studies and analysis of real-world scenarios, this research highlights the benefits and challenges of implementing performance testing in DevOps environments. The findings emphasize the significance of continuous performance validation, real-time monitoring, and iterative optimization to achieve robust and resilient software systems. The outcomes of this research provide valuable insights for software development teams, guiding them in adopting a comprehensive approach to performance testing within DevOps pipelines, ultimately improving the overall quality and performance of software applications.
Keywords
DevOps, Performance testing, Optimization, Pipelines, Software quality.
Reference
[1] Vivek Basavegowda Ramu, “PerfDetectiveAI - Performance Gap Analysis and Recommendation in Software Applications,” SSRG International Journal of Computer Science and Engineering, vol. 10, no. 5, pp. 40-46, 2023.
[CrossRef] [Publisher Link]
[2] H. Sarojadevi, “Performance Testing: Methodologies and Tools,” Journal of Information Engineering and Applications, vol. 1, no. 5, pp. 5-13, 2011.
[Google Scholar] [Publisher Link]
[3] Mayank Gokarna, and Raju Singh, “DevOps: A Historical Review and Future Works,” 2021 International Conference on Computing, Communication, and Intelligent Systems, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Muhammad Owais Khan et al., “Fast Delivery, Continuously Build, Testing and Deployment with DevOps Pipeline Techniques on Cloud,” Indian Journal of Science and Technology, vol. 13, no. 5, pp. 552–575, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Saif Gunja, What is DevOps? Unpacking the Purpose and Importance of an IT Cultural Revolution, Dynatrace News, 2023. [Online]. Available: https://www.dynatrace.com/news/blog/what-is-devops/
[6] Catia Trubiani et al., “Performance Issues? Hey DevOps, Mind the Uncertainty,” IEEE Software, vol. 36, no. 2, pp. 110–117, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Andreas Brunnert et al., “Performance-oriented DevOps: A Research Agenda,” arXiv preprint arXiv:1508.04752, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Jan Waller, Nils C. Ehmke, and Wilhelm Hasselbring, “Including Performance Benchmarks into Continuous Integration to Enable DevOps,” SIGSOFT Software Engineering Notes, vol. 40, no. 2, pp. 1–4, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Jinfu Chen, “Performance Regression Detection in DevOps,” Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Companion Proceedings, pp. 206–209, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Cor-Paul Bezemer et al., “How is Performance Addressed in DevOps?,” Proceedings of the 2019 ACM/SPEC International Conference on Performance Engineering, pp. 45–50, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Pooja Batra, and Aman Jatain, “Measurement Based Performance Evaluation of DevOps,” 2020 International Conference on Computational Performance Evaluation, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Agata Kołtun, and Beata Pańczyk, “Comparative Analysis of web Application Performance Testing Tools,” Journal of Computer Sciences Institute, vol. 17, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Performance Testing Tools, javatpoint. [Online]. Available: https://www.javatpoint.com/performance-testing-tools
[14] Giovanni Denaro, Andrea Polini, and Wakfgang Emmerich, “Early Performance Testing of Distributed Software Applications,” Proceedings of the 4th International Workshop on Software and Performance, pp. 94-103, 2004.
[CrossRef] [Google Scholar] [Publisher Link]
[15] Ferenc Bozoki, and Tibor Csondes, “Scheduling in Performance Test Environment,” 2008 16th International Conference on Software, Telecommunications and Computer Networks, 2008.
[CrossRef] [Publisher Link]
[16] Victor Samoylov, Dmitry Latnikov, and Mikhail Klokov, How to Extend CI Pipelines with Continuous Performance Testing, Grid Dynamics Blog, 2016. [Online]. Available: https://blog.griddynamics.com/how-to-extend-continuous-integration-ci-pipelines-with-continuous-performance-testing-cpt/
[17] Andre de Camargo et al., “An Architecture to Automate Performance Tests on Microservices,” Proceedings of the 18th International Conference on Information Integration and Web-Based Applications and Services, pp. 422-429, 2016.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Mohammad Rizky Pratama, and Dana Sulistiyo Kusumo, “Implementation of Continuous Integration and Continuous Delivery (CI/CD) on Automatic Performance Testing,” 2021 9th International Conference on Information and Communication Technology, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Isaac Dooley, Chee Wai Lee, and Laxmikant V. Kale, “Continuous Performance Monitoring for Large-scale Parallel Applications,” 2009 International Conference on High Performance Computing, 2009.
[CrossRef] [Google Scholar] [Publisher Link]